As Internet of Things (IoT) technologies become more common and web data grows in volume, there is growing evidence that the ability to analyze continuous data is not only valuable but necessary. In fact, those with the ability to capture and analyze massive numbers of independent continuous data streams will have a powerful capability that will help them to power operational intelligence and predictive analytics. A growing number of applications increasingly rely on fast analysis, but tomorrow’s world will be even more dependent on up-to-the-minute consumption of data streams.

 
Today’s typical approaches to capturing and analyzing streaming data cache the data streams and batch them at hourly, daily, or weekly intervals. This approach is not very effective. It doesn't allow the analyst to take advantage of the rapid creation of streaming data in their integrated analytical models.
 
In this webinar, we will examine the increasing prominence of streaming data and the need to acquire, process, and analyze this data in near real time. Some examples include ingesting and processing data from millions of self-driving cars, tens of millions of devices connected in smart cities, or analyzing and instantly using streaming Web data.
 
Attendees will learn about:
 
- Common use cases for streaming analytics
- Cloud computing and streaming data
- Evolving methods of loading streaming data
- Transitioning away from batch-oriented loading

Hora

18:00 - 19:00 hs GMT+1

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